This invention regards an image information apparatus that is used for medical diagnosis related images as well as photographs and medical images containing data about patients in the form of letters, distinguishing ID information from said images containing images of the subjects and ID information, and filing and reproducing said images.
Currently, imaging systems are in use that perform various types of image processing on image information from medical images produced by CT, MRI, and the like on sources such as the body, reproduce and memorize said images, and use said image information to reproduce images of said subjects on photographic materials or into visible images on a CRT.
These image memorizing and reproduction systems memorize images from various modalities (imaging methods and apparatuses for CT, MRI, and the like), and regularly search said image information from memorized image information and reproduce said image information.
The search conditions used in searching image information for medical images consists, generally, of ID such as patient name, ID number, photography date, and birth date, and image information is memorized in coordination with said ID information (electronic information derived by the ID reading section). Said ID is normally composed of kanji characters, kana characters, English letters, numbers, and symbols (hereafter referred to as “letters”) attached at the time of medical imaging.
In general, image information apparatuses manage images by individual ID, and Tokkaihei 10-21365 deals with an apparatus for managing image information that is automatically memorized with both its corresponding ID information and image information containing said ID information. That is, it describes one aspect of the invention, that recognizes ID information derived by the ID reading section from image information containing ID information taken by imaging systems such as CTs and MRIs, and using said ID information as search information, memorizes image information in the memorizing section in correspondence with said ID information.
However, in the case of the aforementioned aspect, if for example the ID reading section were to read the first ID information in correspondence with the first image information, the memorizing apparatus would first memorize the first ID information in correspondence with the first image information. However, even if the ID information read from the second image information were the same as the first ID information, it would be memorized as separate ID information (for example, second ID information) in correspondence with the second image information.
In the case that for a single patient this type of image information which has the same ID information were to be have multiple instances, the memorizing apparatus would create multiple pairs of individual ID information and individual image information (for example, a pair of first ID information and first image information).
Due to this, although there may be multiple images which contain the same ID information, the memorizing apparatus operator must manage image information for each pair described above, causing operations to be excessively cumbersome.
Also, there is the concern that there may be different problems with the actual implementation, in cases where after initial medical imaging has concluded, imaging of the subject is discontinued for some time, or if for whatever reason a subject that needs a separate ID (such as another patient) is not imaged, causing images not to be sent to the memorizing section, leaving ID information and image information in said memorizing section, resulting in misoperation due to excessive burden placed on said memorizing section.
There currently exists as a method of gaining ID information by the ID reading section from images containing ID the template matching method, which uses a template of letters (selectable letters) which compose the ID to be recognized, comparing said template to letters within the image and recognizing said letters. This method matches all templates successively to the area selected for recognition from the image, selecting the template which is the optimal matching result as the recognition result, and if there is no area selected for recognition for an image, progressively staggers the recognition area and performs matching over the entire image.
However, when trying to recognize letters when images and letters are mixed, misrecognition of letters overlapping the image and misrecognition of letters due to flickering caused by noise as explained in FIG. 6 “Example of video noise” is easy. Even in the case of ordinary letters, letters which resemble each other, such as I (capital i), l (lower case L), and 1 (the number one) (hereafter referred to as “similar letters”) have little difference in their evaluation values and are easily misread, leaving recognition results with low credibility.
In this case, the image information will be filed with the corresponding incorrectly recognized ID information, causing difficult later when users attempt to search for said information, and becoming the cause of incorrect prescription due to misdiagnosis.
Tokkaihei 10-21234 proposes a letter recognition apparatus and an image inputting/outputting system using said letter recognition apparatus which sounds a warning signal to its operator when it encounters letters prone to misrecognition during its letter recognition process, requesting verification or correction of the letter detected during letter recognition.
However, the above mentioned letter recognition apparatus requires a determination section to determine whether the results of letter recognition are questionable or not, as well as a warning section to warn the operator, causing the price of the apparatus to be high. In addition, because a warning signal is given simply because the results of letter recognition are questionable, requiring verification or correction by the operator, operation becomes more cumbersome and operating efficiency is decreased.
In order to solve these problems, Tokkaihei 10-134071 describes the section which outputs letter recognition results to the image reproduction section when outputting visual images.
However, the above mentioned method requires to operator to directly observe the image output by said image reproduction section in order to verify if letter recognition is correct or not, and said visual inspection can be a cause of misoperation, in addition to the fact that in the event of operator detection of incorrect recognition, the operator must commence correction of said results, leading to decreased operating efficiency.